Buckets:
twanghcmut/backup-foundation-physics / third_party /diffsynth /examples /flux2 /model_inference /Template-KleinBase4B-ControlNet.py
| from diffsynth.diffusion.template import TemplatePipeline | |
| from diffsynth.pipelines.flux2_image import Flux2ImagePipeline, ModelConfig | |
| import torch | |
| from modelscope import dataset_snapshot_download | |
| from PIL import Image | |
| pipe = Flux2ImagePipeline.from_pretrained( | |
| torch_dtype=torch.bfloat16, | |
| device="cuda", | |
| model_configs=[ | |
| ModelConfig(model_id="black-forest-labs/FLUX.2-klein-base-4B", origin_file_pattern="transformer/*.safetensors"), | |
| ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="text_encoder/*.safetensors"), | |
| ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"), | |
| ], | |
| tokenizer_config=ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="tokenizer/"), | |
| ) | |
| template = TemplatePipeline.from_pretrained( | |
| torch_dtype=torch.bfloat16, | |
| device="cuda", | |
| model_configs=[ModelConfig(model_id="DiffSynth-Studio/Template-KleinBase4B-ControlNet")], | |
| ) | |
| dataset_snapshot_download( | |
| "DiffSynth-Studio/examples_in_diffsynth", | |
| allow_file_pattern=["templates/*"], | |
| local_dir="data/examples", | |
| ) | |
| image = template( | |
| pipe, | |
| prompt="A cat is sitting on a stone, bathed in bright sunshine.", | |
| seed=0, cfg_scale=4, num_inference_steps=50, | |
| template_inputs = [{ | |
| "image": Image.open("data/examples/templates/image_depth.jpg"), | |
| "prompt": "A cat is sitting on a stone, bathed in bright sunshine.", | |
| }], | |
| negative_template_inputs = [{ | |
| "image": Image.open("data/examples/templates/image_depth.jpg"), | |
| "prompt": "", | |
| }], | |
| ) | |
| image.save("image_ControlNet_sunshine.jpg") | |
| image = template( | |
| pipe, | |
| prompt="A cat is sitting on a stone, surrounded by colorful magical particles.", | |
| seed=0, cfg_scale=4, num_inference_steps=50, | |
| template_inputs = [{ | |
| "image": Image.open("data/examples/templates/image_depth.jpg"), | |
| "prompt": "A cat is sitting on a stone, surrounded by colorful magical particles.", | |
| }], | |
| negative_template_inputs = [{ | |
| "image": Image.open("data/examples/templates/image_depth.jpg"), | |
| "prompt": "", | |
| }], | |
| ) | |
| image.save("image_ControlNet_magic.jpg") | |
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